Dividend Yields and Expected Stock Returns: Alternative Procedures for Inference and Measurement
Alternative ways of conducting inference and measurement for long-horizon forecasting are explored with an application to dividend yields as predictors of stock returns. Monte Carlo analysis indicates that the L. Hansen and R. Hodrick (1980) procedure is biased at long horizons, but the alternatives perform better. These include an estimator derived under the null hypothesis as in M. Richardson and T. Smith (1991), a reformulation of the regression as in N. Jegadeesh (1990), and a vector autoregression (VAR) as in J. Campbell and R. Shiller (1988), S. Kandel and R. Stambaugh (1988), and J. Campbell (1991). The statistical properties of long-horizon statistics generated from the VAR indicate interesting patterns in expected stock returns. Article published by Oxford University Press on behalf of the Society for Financial Studies in its journal, The Review of Financial Studies.
Volume (Year): 5 (1992)
Issue (Month): 3 ()
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